Vermont EPSCoR Publications and Products
] . Unraveling Sediment Dynamics Within Watersheds From Patterns in Suspended Sediment-Discharge Rrelationships. In: 2018 GSA (Geological Society of America) Northeastern Section 53rd Annual Meeting. 2018 GSA (Geological Society of America) Northeastern Section 53rd Annual Meeting. Burlington, VT: Geological Society of America (GSA); 2018. Available from: https://gsa.confex.com/gsa/2018NE/meetingapp.cgi/Paper/310311
. Using unmanned aircraft system (UAS) photogrammetry to monitor bank erosion along river corridors. In: Lake Champlain Research Conference. Lake Champlain Research Conference. Burlington, VT: Lake Champlain Basin Program; 2018. Available from: http://www.lcbp.org/water-environment/data-monitoring/lake-champlain-research-conference/
. Application of unmanned aircraft system (UAS) for monitoring bank erosion along river corridors. Geomatics, Natural Hazards and Risk [Internet]. 2019 ;10(1):1285 - 1305. Available from: https://www.tandfonline.com/doi/full/10.1080/19475705.2019.1571533
. Automating the Classification of Hysteresis in Event Concentration-Discharge Relationships. In: SEDHYD 2019. SEDHYD 2019. Reno, NV: SEDHYD, INC.; 2019. Available from: https://www.sedhyd.org/2019/openconf/modules/request.php?module=oc_program&action=view.php&id=70&file=1/70.pdf
. Hydrological Event Detection & Analysis (HEDA) tool for streamflow and water quality time series. CUAHSI Conference on Hydroinformatics [Internet]. 2019 . Available from: https://www.cuahsi.org/uploads/pages/img/2019_Conference_on_Hydroinformatics_Program.pdf
. Optimization of over-summer snow storage at midlatitudes and low elevation. The Cryosphere [Internet]. 2019 ;13(12):3367 - 3382. Available from: https://www.the-cryosphere.net/13/3367/2019/
. Unmanned Aircraft System (UAS) Photogrammetry for Tracking Streambank Erosion and Geomorphic Change along a Protected River Corridor. In: Eighth International Conference on Case Histories in Geotechnical Engineering. Eighth International Conference on Case Histories in Geotechnical Engineering. Philadelphia, PA: Geo-Institute of ASCE (American Society of Civil Engineers); 2019. Available from: https://ascelibrary.org/doi/10.1061/9780784482070.015
Critical Zone network cluster research: Using Big Data approaches to assess ecohydrological resilience across scales. In: 2020 AGU (American Geophysical Union) Fall Meeting. 2020 AGU (American Geophysical Union) Fall Meeting. Virtual: American Geophysical Union (AGU); 2020. Available from: https://agu.confex.com/agu/fm20/webprogram/Paper748076.html
. A Monitoring Tool for Analyzing Sediment Dynamics Using Water Turbidity Sensor Data. 2020 AGU (American Geophysical Union) Fall Meeting [Internet]. 2020 . Available from: https://agu.confex.com/agu/fm20/webprogram/Paper748005.html
. Quantifying Nutrient Reductions Achieved by Erosion Remediation Projects on Vermont's Roads. 2020 VTrans Research and Innovation Symposium [Internet]. 2020 . Available from: https://vtrans.vermont.gov/planning/research/2020-symposium/env2
. Watershed data science at the event scale: Machine learning for event concentration-discharge analysis. Virtual Summit: Incorporating Data Science and Open Science Techniques in Aquatic Research [Internet]. 2020 . Available from: https://freshwaterecology.wordpress.com/2020/07/08/conference-workshop-virtual-summit-incorporating-data-science-and-open-science-techniques-in-aquatic-research/
. Watershed data science at the event scale: Revealing insights in watershed function through analysis of concentration-discharge relationships. In: 2020 AGU (American Geophysical Union) Fall Meeting. 2020 AGU (American Geophysical Union) Fall Meeting. Virtual: American Geophysical Union (AGU); 2020. Available from: https://agu.confex.com/agu/fm20/webprogram/Paper766889.html
. Multivariate event time series analysis using hydrological and suspended sediment data. Journal of Hydrology [Internet]. 2021 ;593:125802. Available from: https://www.sciencedirect.com/science/article/pii/S0022169420312634
. Data Imputation for Multivariate Time Series Sensor Data With Large Gaps of Missing Data. IEEE Sensors Journal [Internet]. 2022 ;22(11):10671 - 10683. Available from: https://ieeexplore.ieee.org/document/9755143